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Scientific Engineer Jobs (NOW HIRING)

Deloitte

Senior AI Engineer - SFL Scientific

Los Angeles, CA · On-site

$112K - $154K/yr

Required : • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience • 4+ years of experience working in data engineering, data science, software ...

Viridien

Scientific Software Developer

Houston, TX · Hybrid

Master's degree or higher in Physics, Engineering, Mathematics, or Computer Science, or 5 years of hands-on experience in scientific programming * Fluency in C/C++ (Fortran also preferred)

Viridien

Scientific Software Developer

Houston, TX · Hybrid

Master's degree or higher in Physics, Engineering, Mathematics, or Computer Science, or 5 years of hands-on experience in scientific programming * Fluency in C/C++ (Fortran also preferred)

Cgg

Scientific Software Developer

Houston, TX · Hybrid

Master's degree or higher in Physics, Engineering, Mathematics, or Computer Science, or 5 years of hands-on experience in scientific programming * Fluency in C/C++ (Fortran also preferred)

Datacor

Senior Scientific Programmer

Partner with the founding engineer to formalize existing modeling, QA, and support methodology ... Requirements * Masters or PhD level in science or engineering, with outstanding academic ...

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Scientific Engineer information

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$30K

$95.9K

$173K

How much do scientific engineer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for scientific engineer in the United States is $95,930.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,500.00 and $120,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a scientific engineer, and why are they important?

To thrive as a Scientific Engineer, you need a solid background in engineering principles, scientific analysis, and typically a degree in engineering or a related field. Familiarity with simulation software, laboratory instrumentation, and data analysis tools, as well as relevant certifications, is often required. Strong analytical thinking, problem-solving abilities, and effective communication skills set candidates apart in this role. These skills and qualities are crucial for developing innovative solutions, ensuring precise experimentation, and collaborating on multidisciplinary projects.

What is the difference between Scientific Engineer vs Mechanical Engineer?

AspectScientific EngineerMechanical Engineer
Required CredentialsBachelor's or higher in engineering, physics, or related fields; often includes research experienceBachelor's or higher in mechanical engineering or related disciplines
Work EnvironmentResearch labs, R&D departments, technical development projectsDesign, manufacturing, testing, and maintenance in industrial settings
Industry UsageResearch institutions, aerospace, defense, scientific organizationsAutomotive, manufacturing, energy, robotics

Scientific Engineers focus on research, development, and applying scientific principles to solve complex problems, often working in labs or research settings. Mechanical Engineers typically design, analyze, and manufacture mechanical systems in industrial environments. While both roles require engineering degrees, their work environments and primary objectives differ, with Scientific Engineers emphasizing research and innovation, and Mechanical Engineers focusing on practical design and production.

What is a scientific engineer?

Scientific engineers are professionals who apply principles of science and engineering to solve complex technical problems, often in research and development settings. They bridge the gap between scientific discoveries and practical applications, designing experiments, developing prototypes, and refining processes. Scientific engineers work in various industries, including pharmaceuticals, aerospace, energy, and environmental science, collaborating with scientists and other engineers to innovate and improve technology. Their role is essential in turning theoretical knowledge into real-world solutions that advance scientific progress.

How does a scientific engineer typically collaborate with researchers and other specialists within multidisciplinary teams?

Scientific Engineers frequently work alongside researchers, data analysts, and subject-matter experts to develop and implement experimental designs, prototypes, or technical solutions. Collaboration often involves translating scientific requirements into practical engineering tasks, troubleshooting technical challenges, and communicating progress in regular meetings. This cross-functional teamwork ensures that engineering solutions effectively support research objectives, and it offers opportunities to learn from diverse perspectives within the team. Such collaboration is essential for advancing complex projects and achieving innovative outcomes in scientific settings.

What cities are hiring for Scientific Engineer jobs?

Cities with the most Scientific Engineer job openings:

What states have the most Scientific Engineer jobs?

States with the most job openings for Scientific Engineer jobs include:

Scientific Engineer jobs near you
Infographic showing various Scientific Engineer job openings in the United States as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $95,930 per year, or $46.1 per hour.

Senior AI Engineer - SFL Scientific

Deloitte

Los Angeles, CA • On-site

$112K - $154K/yr

Full-time

Re-posted 19 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

44th of 150 rated financial services

Job description

Job Summary:
Deloitte is a leading professional services firm, and they are seeking a Senior AI Engineer to join their Strategy & Transactions team. In this role, you will work cross-functionally to develop robust AI infrastructure and deployment services for machine learning applications, while leveraging advanced technical skills in data architecture and engineering.
Responsibilities:
• Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
• Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
• Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
• Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
• Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
• Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
• Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
• Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
• Mentor, motivate, and coach junior members on technical best practices and inspire professional development
Qualifications:
Required:
• Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
• 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
• 4+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
• 4+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
• 2+ years of experience managing teams in technical delivery and delivering complex and critical projects
• 2+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins
• 2+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
• 2+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
• Live within commuting distance to one of Deloitte's consulting offices
• Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
• Limited immigration sponsorship may be available
Preferred:
• Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
• AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
• 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack
Company:
Deloitte is a business consulting company that offers audit, consulting, financial advisory, and tax services. Founded in 1845, the company is headquartered in London, GBR, with a team of 10001+ employees. The company is currently Late Stage.

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